code: def test_train(self):
      x = np.random.random([32, 10])
      y = np.random.random(
          [
              32,
          ]
      )
      model = BSequential()
      model.add(BLayer.Dense(5, input_shape=(10,)))
      model.compile(optimizer="sgd", loss="mse", metrics=["accuracy"])
      model.fit(x, y, batch_size=8, nb_epoch=2, validation_data=(x, y))
      model.evaluate(x, y, batch_size=8)
      model.predict(x)
  
imports: import pytest
  from test.bigdl.test_utils import BigDLTestCase
  import bigdl.dllib.nn.keras.layers.layer
  import keras.layers
  import keras.backend
  from bigdl.dllib.keras.converter import WeightsConverter
  from bigdl.dllib.feature.dataset.dataset import *
  from bigdl.dllib.nn.keras.layers.topology import Model
  from bigdl.dllib.nn.keras.layers.topology import Sequential
  from keras.engine import merge, Model
  from keras.models import Sequential
label_desc: Use image node_id 12 for calling the TestKerasAPI obj's underlying member method code with example usage: obj.test_train() without return types